Action Recognition Sample (gst-launch command line)

This sample demonstrates action recognition pipeline constructed via gst-launch-1.0 command-line utility.

How It Works

The sample utilizes GStreamer command-line tool gst-launch-1.0 which can build and run GStreamer pipeline described in a string format. The string contains a list of GStreamer elements separated by exclamation mark !, each element may have properties specified in the format property=value.

This sample builds GStreamer pipeline of the following elements

  • filesrc or urisourcebin or v4l2src for input from file/URL/web-camera
  • decodebin for video decoding
  • videoconvert/vaapipostproc for converting video frame into different color formats for system and GPU memory
  • gvaactionrecognitionbin for action recognition based on OpenVINO™ Toolkit Inference Engine
  • gvawatermark for labels visualization
  • gvafpscounter for rendering fps info in terminal
  • fpsdisplaysink for rendering output video into screen

    NOTE: sync=false property in fpsdisplaysink element disables real-time synchronization so pipeline runs as fast as possible

    Models

The sample uses by default the following pre-trained models from OpenVINO™ Toolkit Open Model Zoo

  • action-recognition-0001-encoder encoder part of action recognition
  • action-recognition-0001-decoder decoder part of action recognition

NOTE: Before running samples (including this one), run script download_models.sh once (the script located in samples top folder) to download all models required for this and other samples.

The sample contains model_proc subfolder with .json file with description of input/output formats and post-processing rules for action recognition models.

Running

./action_recognition.sh INPUT_VIDEO [DEVICE] [SINK_ELEMENT]

The sample takes three command-line parameters:

  1. [INPUT_VIDEO] to specify input video file (required). The input could be
  • local video file
  • web camera device (ex. /dev/video0)
  • RTSP camera (URL starting with rtsp://) or other streaming source (ex URL starting with http://)
  1. [DEVICE] to specify device for inference (optional). Please refer to OpenVINO™ toolkit documentation for supported devices. https://docs.openvinotoolkit.org/latest/openvino_docs_IE_DG_supported_plugins_Supported_Devices.html You can find what devices are supported on your system by running following OpenVINO™ toolkit sample: https://docs.openvinotoolkit.org/latest/openvino_inference_engine_ie_bridges_python_sample_hello_query_device_README.html
  2. [SINK_ELEMENT] to choose between render mode and fps throughput mode (optional):
    • display - render (default)
    • fps - FPS only

Sample Output

The sample

  • prints gst-launch-1.0 full command line into console
  • starts the command and either visualizes video with action text labels or prints out fps if you set SINK_ELEMENT = fps

See also